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Algorithmic Foundations of Robotics XIII

Proceedings of the 13th Workshop on the Algorithmic Foundations of Robotics

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Marco Morales

    1. Departamento de Sistemas Digitales, Instituto Tecnológico Autónomo de México, México, Mexico

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  2. Lydia Tapia

    1. Department of Computer Science, University of New Mexico, Albuquerque, USA

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  3. Gildardo Sánchez-Ante

    1. Universidad Politécnica de Yucatán, Yucatán, Mexico

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  4. Seth Hutchinson

    1. Georgia Tech, Atlanta, USA

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  • Highlights the latest research on robotic algorithms
  • Gathers the edited outcomes of the 13th International Workshop on the Algorithmic Foundations of Robotics (WAFR), held at Universidad Politécnica de Yucatán in Mérida, México on December 9–11, 2018
  • Written by leading experts in the field

Part of the book series: Springer Proceedings in Advanced Robotics (SPAR, volume 14)

Included in the following conference series:

Conference proceedings info: WAFR 2018.

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Table of contents (54 papers)

  1. Front Matter

    Pages i-xxii
    Download chapter PDF

  2. General Tools for Motion Planning

    1. Front Matter

      Pages 1-1
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    2. Path Planning for Ellipsoidal Robots and General Obstacles via Closed-Form Characterization of Minkowski Operations

      • Sipu Ruan, Qianli Ma, Karen L. Poblete, Yan Yan, Gregory S. Chirikjian
      Pages 3-18

    3. Free Space of Rigid Objects: Caging, Path Non-existence, and Narrow Passage Detection

      • Anastasiia Varava, J. Frederico Carvalho, Florian T. Pokorny, Danica Kragic
      Pages 19-35

    4. Fast Collision Detection for Motion Planning Using Shape Primitive Skeletons

      • Mukulika Ghosh, Shawna Thomas, Nancy M. Amato
      Pages 36-51

    5. Fast Swept Volume Estimation with Deep Learning

      • Hao-Tien Lewis Chiang, Aleksandra Faust, Satomi Sugaya, Lydia Tapia
      Pages 52-68

    6. Concurrent Nearest-Neighbor Searching for Parallel Sampling-Based Motion Planning in SO(3), SE(3), and Euclidean Spaces

      • Jeffrey Ichnowski, Ron Alterovitz
      Pages 69-85

  3. Data Structures for Motion Planning

    1. Front Matter

      Pages 87-87
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    2. A Visibility-Based Approach to Computing Nondeterministic Bouncing Strategies

      • Alexandra Q. Nilles, Yingying Ren, Israel Becerra, Steven M. LaValle
      Pages 89-105

    3. Finding Plans Subject to Stipulations on What Information They Divulge

      • Yulin Zhang, Dylan A. Shell, Jason M. O’Kane
      Pages 106-124

  4. Planning Under Uncertainty

    1. Front Matter

      Pages 125-125
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    2. Online Partial Conditional Plan Synthesis for POMDPs with Safe-Reachability Objectives

      • Yue Wang, Swarat Chaudhuri, Lydia E. Kavraki
      Pages 127-143

    3. An Approximation Algorithm for Risk-Averse Submodular Optimization

      • Lifeng Zhou, Pratap Tokekar
      Pages 144-159

    4. Pushing Fast and Slow: Task-Adaptive Planning for Non-prehensile Manipulation Under Uncertainty

      • Wisdom C. Agboh, Mehmet R. Dogar
      Pages 160-176

  5. Imitation Learning

    1. Front Matter

      Pages 177-177
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    2. Learning Stabilizable Dynamical Systems via Control Contraction Metrics

      • Sumeet Singh, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone
      Pages 179-195

    3. Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models

      • Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox et al.
      Pages 196-211

    4. A Dynamic Regret Analysis and Adaptive Regularization Algorithm for On-Policy Robot Imitation Learning

      • Jonathan N. Lee, Michael Laskey, Ajay Kumar Tanwani, Anil Aswani, Ken Goldberg
      Pages 212-227

    5. Learning Constraints from Demonstrations

      • Glen Chou, Dmitry Berenson, Necmiye Ozay
      Pages 228-245

    6. Probability-Weighted Temporal Registration for Improving Robot Motion Planning and Control Learned from Demonstrations

      • Chris Bowen, Ron Alterovitz
      Pages 246-263
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  1. Algorithmic Foundations of Robotics XIII

Keywords

About this book

This book gathers the outcomes of the thirteenth Workshop on the Algorithmic Foundations of Robotics (WAFR), the premier event for showcasing cutting-edge research on algorithmic robotics. The latest WAFR, held at Universidad Politécnica de Yucatán in Mérida, México on December 9–11, 2018, continued this tradition. This book contains fifty-four papers presented at WAFR, which highlight the latest research on fundamental algorithmic robotics (e.g., planning, learning, navigation, control, manipulation, optimality, completeness, and complexity) demonstrated through several applications involving multi-robot systems, perception, and contact manipulation. Addressing a diverse range of topics in papers prepared by expert contributors, the book reflects the state of the art and outlines future directions in the field of algorithmic robotics.

Editors and Affiliations

  • Departamento de Sistemas Digitales, Instituto Tecnológico Autónomo de México, México, Mexico

    Marco Morales

  • Department of Computer Science, University of New Mexico, Albuquerque, USA

    Lydia Tapia

  • Universidad Politécnica de Yucatán, Yucatán, Mexico

    Gildardo Sánchez-Ante

  • Georgia Tech, Atlanta, USA

    Seth Hutchinson

Bibliographic Information

  • Book Title: Algorithmic Foundations of Robotics XIII

  • Book Subtitle: Proceedings of the 13th Workshop on the Algorithmic Foundations of Robotics

  • Editors: Marco Morales, Lydia Tapia, Gildardo Sánchez-Ante, Seth Hutchinson

  • Series Title: Springer Proceedings in Advanced Robotics

  • DOI: https://doi.org/10.1007/978-3-030-44051-0

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: Springer Nature Switzerland AG 2020

  • Hardcover ISBN: 978-3-030-44050-3Published: 08 May 2020

  • Softcover ISBN: 978-3-030-44312-2Published: 08 May 2021

  • eBook ISBN: 978-3-030-44051-0Published: 07 May 2020

  • Series ISSN: 2511-1256

  • Series E-ISSN: 2511-1264

  • Edition Number: 1

  • Number of Pages: XXII, 959

  • Number of Illustrations: 154 b/w illustrations, 308 illustrations in colour

  • Topics: Robotics and Automation, Computational Intelligence, Robotics

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